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NASA NTRS2010

Risk Analysis of On-Orbit Spacecraft Refueling Concepts

On-orbit refueling of spacecraft has been proposed as an alternative to the exclusive use of Heavy-lift Launch Vehicles to enable human exploration beyond Low Earth Orbit (LEO). In these scenarios, beyond LEO spacecraft are launched dry (without propellant) or partially dry into orbit, using smaller or fewer element launch vehicles. Propellant is then launched into LEO on separate launch vehicles and transferred to the spacecraft. Refueling concepts are potentially attractive because they reduce the maximum individual payload that must be placed in Earth orbit. However, these types of approaches add significant complexity to mission operations and introduce more uncertainty and opportunities for failure to the mission. In order to evaluate these complex scenarios, the authors developed a Monte Carlo based discrete-event model that simulates the operational risks involved with such strategies, including launch processing delays, transportation system failures, and onorbit element lifetimes. This paper describes the methodology used to simulate the mission risks for refueling concepts, the strategies that were evaluated, and the results of the investigation. The results of the investigation show that scenarios that employ refueling concepts will likely have to include long launch and assembly timelines, as well as the use of spare tanker launch vehicles, in order to achieve high levels of mission success through Trans Lunar Injection.

Cirillo, William M.↗

NASA NTRSDate not supplied

Heat Transfer Analysis in Wire Bundles for Aerospace Vehicles

Design of wiring for aerospace vehicles relies on an understanding of "ampacity" which refers to the current carrying capacity of wires, either, individually or in wire bundles. Designers rely on standards to derate allowable current flow to prevent exceedance of wire temperature limits due to resistive heat dissipation within the wires or wire bundles. These standards often add considerable margin and are based on empirical data. Commercial providers are taking an aggressive approach to wire sizing which challenges the conventional wisdom of the established standards. Thermal modelling of wire bundles may offer significant mass reduction in a system if the technique can be generalized to produce reliable temperature predictions for arbitrary bundle configurations. Thermal analysis has been applied to the problem of wire bundles wherein any or all of the wires within the bundle may carry current. Wire bundles present analytical challenges because the heat transfer path from conductors internal to the bundle is tortuous, relying on internal radiation and thermal interface conductance to move the heat from within the bundle to the external jacket where it can be carried away by convective and radiative heat transfer. The problem is further complicated by the dependence of wire electrical resistivity on temperature. Reduced heat transfer out of the bundle leads to higher conductor temperatures and, hence, increased resistive heat dissipation. Development of a generalized wire bundle thermal model is presented and compared with test data. The steady state heat balance for a single wire is derived and extended to the bundle configuration. The generalized model includes the effects of temperature varying resistance, internal radiation and thermal interface conductance, external radiation and temperature varying convective relief from the free surface. The sensitivity of the response to uncertainties in key model parameters is explored using Monte Carlo analysis.

S L Rickman↗

NASA NTRS2015

Trajectory Dispersion Control for the Cassini Grand Finale Mission

The Cassini Grand Finale Mission, which consists of 22 ballistic orbits, will begin on April 22, 2017 after the last targeted Titan flyby. It will end on September 15, 2017 when the spacecraft dives into Saturn's atmosphere and be permanently captured. High volumes of unique science data from various onboard instruments are expected from the mission. To ensure its success and facilitate science planning, the trajectory dispersion needs to be controlled below 250 km (root-mean-square spatial deviation at the 68th percentile level) for a few segments of trajectory in the mission. This paper reports the formulation and solution of this dispersion control problem. We consider various sources of uncertainties including flyby error, orbit determination error, maneuver execution error, thruster firing control error, and uncertainty in Saturn's atmospheric model. A non-linear Monte Carlo Trajectory Dispersion tool is developed and employed for the analysis. It is found that a total of three Orbit Trim Maneuvers with a 99% (Delta)V usage of less than 2 m/s will adequately control the trajectory.

orbit determination↗

NASA NTRSDate not supplied

TPSAS-NF1676L-17560-DND

There has been much work in the past few years updating direct simulation Monte Carlo (DSMC) algorithms and phenomenological models. Algorithmic advances[1] have allowed simulations to be run more efficiently reducing the time to solution as well as allowing simulations to be run at lower altitudes because of the increased efficiency. Improved phenomenological models have focused on chemistry[2, 3] and internal energy modes[4, 5] and have had a profound effect on DSMC simulations by way of expanded physical realism[6] and computational speed. The DAC software[7, 8] has been widely adopted and performs well the jobs it was designed to do, but upgrading DAC to take advantage of these modeling advances has proven difficult due to a lack of modularity in the code base. Agency investment in DSMC code development has been almost non-existent for the past two decades. DAC was developed in the 1990?s at LaRC and has seen little improvement since. However, NASA is currently (under the Hypersonics Entry, Descent and Landing program) investing in the possibility of a stand-alone code to incorporate recent developments to expand physical realism, time to solution, and expand the range of usefulness of DSMC (both in velocity space and altitude).

Derek S Liechty↗

NASA NTRS2001

Radiation breakage of DNA: a model based on random-walk chromatin structure

Monte Carlo computer software, called DNAbreak, has recently been developed to analyze observed non-random clustering of DNA double strand breaks in chromatin after exposure to densely ionizing radiation. The software models coarse-grained configurations of chromatin and radiation tracks, small-scale details being suppressed in order to obtain statistical results for larger scales, up to the size of a whole chromosome. We here give an analytic counterpart of the numerical model, useful for benchmarks, for elucidating the numerical results, for analyzing the assumptions of a more general but less mechanistic "randomly-located-clusters" formalism, and, potentially, for speeding up the calculations. The equations characterize multi-track DNA fragment-size distributions in terms of one-track action; an important step in extrapolating high-dose laboratory results to the much lower doses of main interest in environmental or occupational risk estimation. The approach can utilize the experimental information on DNA fragment-size distributions to draw inferences about large-scale chromatin geometry during cell-cycle interphase.

Chromatin/radiation effects↗

NASA NTRS2017

Investigation of the High-Energy Oxidation of FiberForm from DSMC Analysis of Molecular Beam Experiments

A collaborative effort between the University of Illinois at Urbana-Champaign (UIUC), NASA Ames Research Center (ARC) and Montana State University (MSU) succeeded at developing a new finite-rate carbon oxidation model from molecular beam scattering experiments on vitreous carbon (VC). We now aim to use the direct simulation Monte Carlo (DSMC) code SPARTA to apply the model to each fiber of the porous fibrous Thermal Protection Systems (TPS) material FiberForm (FF). The detailed micro-structure of FF was obtained from X-ray micro-tomography and then used in DSMC. Both experiments and simulations show that the CO/O products ratio increased at all temperatures from VC to FF. We postulate this is due to the larger number of collisions an O atom encounters inside the porous FF material compared to the flat surface of VC. For the simulations, we particularly focused on the lowest and highest temperatures studied experimentally, 1023 K and 1823 K, and found good agreement between the finite-rate DSMC simulations and experiments.

Oxidation↗

NASA NTRS2021

A Study into Validating a Coupled Method of Characteristics and Direct Simulation Monte Carlo Method Against Empirical Data

The following will outline the methodology and results of validating a coupled Method of Characteristics (MOC) and Direct Simulation Monte Carlo (DSMC) method. This research focused specifically on modeling plume impingement, induced by Reaction Control System (RCS) thrusters that flew on the National Aeronautics and Space Administration’s (NASA’s) space shuttle Discovery. For each simulation, the continuum portion of the RCS thruster was simulated using MOC for solving hyperbolic Partial Differential Equations (PDEs) and computed with the NASA code, Reacting and Multi-phase Program (RAMP). The solution was then implemented as a starting condition into the NASA DSMC code, Direct Simulation and Monte Carlo Analysis Code (DAC). Typically, DSMC models rely on code-to-code validation for fidelity. The significance of this research is in its ability to validate its models against empirical data. Prior to computing solutions for these simulations, the mesh size and structure were optimized and many variants of DSMC input parameters were iterated on in order to acquire a reliable, mesh-independent, fully optimized numerical solution. This research will discuss the mathematical formulation of MOC for nozzle flow and DSMC for rarefied gases. Additionally, it will provide an explanation of how to implement these mathematical concepts into the two solvers: RAMP and DAC. Ultimately, this research will demonstrate that the overall process illustrated produces results in good agreement with empirical data. As a consequence, the methodology presented is granted an increased level of confidence and will greatly contribute to the aerospace industry and its effort in understanding and predicting rarefied flow fields.

Direct Simulation Monte Carlo Analysis Code↗

NASA NTRS1990

An infrared sky model based on the IRAS point source data

A detailed model for the infrared point source sky is presented that comprises geometrically and physically realistic representations of the galactic disk, bulge, spheroid, spiral arms, molecular ring, and absolute magnitudes. The model was guided by a parallel Monte Carlo simulation of the Galaxy. The content of the galactic source table constitutes an excellent match to the 12 micrometer luminosity function in the simulation, as well as the luminosity functions at V and K. Models are given for predicting the density of asteroids to be observed, and the diffuse background radiance of the Zodiacal cloud. The model can be used to predict the character of the point source sky expected for observations from future infrared space experiments.

Cohen, Martin↗

NASA NTRS2014

Path Toward a Unifid Geometry for Radiation Transport

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Lee, Kerry↗

NASA NTRS2026

Hybrid Modeling Study on Grain Evolution in the Metal Welding Process and Its Potential Lunar Application

Metal is most commonly used structural material in a wide range of spacecraft, and welding is the principal method for joining metal components into functional systems. However, conducting welding experiments under extreme environments—such as microgravity or vacuum conditions in space—is prohibitively expensive and experimentally challenging. To overcome these limitations, multi-physics computational welding models provide a cost-effective and versatile alternative. In this work, the authors have developed a coupled thermal (fluid) microstructure simulation framework to model metal welding under varying gravity conditions. The framework integrates a mixed-mode heat transfer formulation (conduction, convection, and radiation) with molten pool fluid dynamics, enabling accurate prediction of temperature fields and weld-pool geometry. A grain growth model is further incorporated to capture the spatial and temporal evolution of microstructure, including grain size distribution and morphological transitions during solidification. This approach provides detailed insight into molten pool evolution and grain-level microstructure development throughout the welding process. By explicitly parameterizing environmental conditions, the model supports extrapolation to off-Earth manufacturing scenarios such as welding on the lunar surface. Tantalum—chosen in this study due to its high melting point, oxidation resistance, and mechanical stability at elevated temperatures—serves as the material system for model demonstration. Beyond Tantalum, the integrated multi-physics framework offers broad applicability for predictive welding simulations of various structural and refractory metals or alloys used in extreme terrestrial or extraterrestrial environments.

kinetic Monte Carlo (SPPARKS)↗

NASA NTRS1994

Cosmic temperature fluctuations from two years of COBE differential microwave radiometers observations

The first two years of Cosmic Background Explorer (COBE) Differential Microwave Radiometers (DMR) observations of the cosmic microwave background (CMB) anisotropy are analyzed and compared with our previously published first year results. The results are consistent, but the addition of the second year of data increases the precision and accuracy detected CMB temperature fluctuations. The 2 yr 53 GHz data are characterized by rms temperature fluctuations of (delta-T)(sub rms) (7 deg) = 44 +/- 7 micro-K and (delta-T)(sub rms) (10 deg) = 30.5 +/- 2.7 micro-K at 7 deg and 10 deg angular resolution, respectively. The 53 x 90 GHz cross-correlation amplitude at zero lag is C(0)(sup 1/2) = 36 +/- 5 micro-K (68% CL) for the unsmoothed (7 deg resolution) DMR data. We perform a likelihood analysis of the cross-correlation function, with Monte Carlo simulations to infer biases of the method, for a power-law model of initial density fluctuations, P(k) proportional to R(exp n). The Monte Carlo simulations indicate that derived estimates of n are biased by +0.11 +/- 0.01, while the subset of simulations with a low quadrupole (as observed) indicate a bias of +0.31+/- 0.04. Derived values for 68% confidence intervals are given corrected (and not corrected) for our estimated biases. Including the quadrupole anisotropy, the most likely quadrupole-normalized amplitude is Q(sub rms-PS) = 14.3(sup + 5.2 sub -3.3) micro-K (12.8(sup + 5.2 sub -3.3) micro-K0 with a spectral index n = 1.42(sup + 0.49 sub -0.55)(n = 1.53(sup + 0.49 sub -0.55). With n fixed to 1.0 the most likely amplitude is 18.2 +/- 11.5 micro-K (17.4 +/- 1.5 micro-K). The marginal likelihood of n is 1.42 +/- 0.37 (1.53 +/- 0.37). Excluding the quadrupole anisotropy, the most likely quadrupole-normalized amplitude is Q(sub rms-PS) = 17.4(sup + 7.5 sub -5.2) micro-K (15.8(sup + 7.5 sub -5.2) micro-K) with a spectral index n = 1.11(sup + 0.60 sub -0.55) (n = 1.22(sup + 0.60 sub -0.55). With n fixed to 1.0 the most likely amplitude is 18.6 +/- 1.6 micro-K (18.2 +/- 1.6 micro-K). The marginal likelihood of n is 1.11 +/- 0.40 (1.22 +/- 0.40). Our best estimate of the dipole from the 2 yr DMR data is 3.363 +/- 0.024 mK toward Galactic coordinates (l, b) = (264.4 deg +/- 0.2 deg, 48.1 deg +/- 0.4 deg), and our best estimate of the rms quadrupole amplitude in our sky is 6 +/- 3 micro-K (68% CL).

Bennett, C. L.↗

NASA NTRS1978

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Deepak, A.↗

NASA NTRS2018

Detection of Photospheric Features in the Near-Infrared Spectrum of a Class 0 Protostar

We present a near-infrared K-band R ≃ 1500 Keck spectrum of S68N, a Class 0 protostar in the Serpens molecular cloud. The spectrum shows a very red continuum, CO absorption bands, weak or non-existent atomic metal absorptions, and H2 emission lines. The near-IR H2 emission is consistent with excitation in shocks or by X-rays but not by UV radiation. We model the absorption component as a stellar photosphere plus circumstellar continuum emission with wavelength-dependent extinction. A Markov Chain Monte Carlo analysis shows that the most likely model parameters are consistent with a low-temperature, low-gravity photosphere with signifi cant extinction and no more than modest continuum veiling. Its T(eff) ≃ 3260 K effective temperature is similar to that of older, more evolved pre-main-sequence stars, but its surface gravity log g ≃ 2:4 cm/sq.s is approximately 1 dex lower. This implies that the radius of this protostar is a factor of ~ 3 larger than that of 106 yr old T Tauri stars. Its low veiling is consistent with a circumstellar disk having intrinsic near-IR emission that is less than or equal to that of more evolved Class I protostars. Along with the high extinction, this suggests that most of the circumstellar material is in a cold envelope, as expected for a Class 0 protostar. This is the first known detection and analysis of a Class 0 protostar absorption spectrum.

Thomas P Greene↗

NASA NTRS2021

A Study into Validating A Coupled Method of Characteristics And Direct Simulation Monte Carlo Method Against Empirical Data

DAC↗

NASA NTRS2020

Dust and gas absorption in the High Mass X-ray Binary IGR J16318−4848

Context. With an absorption column density on the order of 10(exp 24)per sq. cm, IGR J16318-4848 is one of the most extreme cases of a highly obscured High Mass X-ray Binary. Besides the overall continuum absorption, the source spectrum exhibits a strong iron and nickel fluorescence line complex at 6.4 keV. Previous empirical modeling of these features and comparison with radiative transfer simulations raised questions about the structure and covering fraction of the absorber and the profile of the fluorescence lines. Aims. We aim at a self-consistent description of the continuum absorption, the absorption edges and the fluorescent lines to constrain properties of the absorbing material, such as ionization structure and geometry. We further investigate the effects of dust absorption on the observed spectra and the possibility of fluorescent emission from dust grains. Methods. We use XMM-Newton and NuSTAR spectra to first constrain empirically the incident continuum and fluorescence lines. Next, we use XSTAR to construct a customized photoionization model where we vary the ionization parameter, column density, and covering fraction. In a third step, we model the absorption and fluorescence in a dusty olivine absorber and employ both, a simple analytical model for the fluorescent line emission and Monte Carlo radiative transfer, spectral shapes and line fluxes that are very close to the data are generated. Results. Our empirical spectral modeling is in agreement with previous works. Our second model, the single gas absorber does not describe the observational data. In particular, irrespective of the ionization state or column density of the absorber, a much higher covering fraction than previously estimated is needed to produce the strong fluorescence lines and the large continuum absorption. A dusty, spherical absorber (modeled as consisting of olivine dust, although the nature of dust cannot be constrained) is well able to produce the observed continuum absorption and edges. Conclusions. A dense, dusty absorber in the direct vicinity of the source consisting of dust offers a consistent description of both the strong continuum absorption and the strong emission features in the X-ray spectrum of IGR J16318􀀀4848. In particular, for low optical depth of individual grains the dust will contribute significantly to the fluorescent emission, which is the case for typical densities and grain size distribution models.

Ralf Ballhausen↗

NASA NTRS2023

Applicability of the Nasa Galactic Cosmic Ray Simulator for Mice, Rats, and Minipigs

Space radiation poses multiple health risks to astronauts including cancer, cardiovascular disease, and damage to the central nervous system. Radiation from galactic cosmic rays (GCR) is the main source of these risks for missions beyond low Earth orbit to the moon and beyond. A galactic cosmic ray simulator (GCRsim) was developed at the NASA Space Radiation Laboratory to better understand and mitigate these risks by simulating the complex mixed field of the GCR environment at a ground-based facility. The GCRsim delivers a radiation field to cell and animal models in a laboratory setting that is comparable to the shielded radiation environment within internal organs of astronauts in deep space missions. Previous verification studies using Monte Carlo simulations with mouse (Digimouse) and rat (Digirat) digital phantoms showed that the GCRsim yields acceptable dose homogeneity within the internal organs of these animals. Spectral characteristics of the intended space radiation environment are also accurately reproduced at radiosensitive sites in both phantoms. In this work, similar Monte Carlo simulations were performed in a minipig model (Digipig) to show the applicability and limitations of the current GCRsim for larger animal model systems. The results showed dose homogeneity in internal organs of the three animal models with GCRsim irradiation. While slightly lower average doses were seen in the minipig compared to the external beam dose, the individual voxel doses in slices of the phantoms were found to be within 6%–8% of the average voxel dose, establishing that the GCRsim can still provide a relatively homogeneous irradiation within larger animals. Furthermore, simulated dose and fluence spectral results across the relevant linear energy transfer (LET) range agreed well with the reference field in the most relevant regions of the spectra, further verifying that the GCRsim beam represents the reference field in larger animals.

Galactic cosmic rays↗

NASA NTRS2016

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

Probability Theory↗

NASA NTRS2017

A Dose of Reality: Radiation Analysis for Realistic Human Spacecraft

INTRODUCTION As with most computational analyses, a tradeoff exists between problem complexity, resource availability and response accuracy when modeling radiation transport from the source to a detector. The largest amount of analyst time for setting up an analysis is often spent ensuring that any simplifications made have minimal impact on the results. The vehicle shield geometry of interest is typically simplified from the original CAD design in order to reduce computation time, but this simplification requires the analyst to "re-draw" the geometry with a limited set of volumes in order to accommodate a specific radiation transport software package. The resulting low-fidelity geometry model cannot be shared with or compared to other radiation transport software packages, and the process can be error prone with increased model complexity. The work presented here demonstrates the use of the DAGMC (Direct Accelerated Geometry for Monte Carlo) Toolkit from the University of Wisconsin, to model the impacts of several space radiation sources on a CAD drawing of the US Lab module. METHODS The DAGMC toolkit workflow begins with the export of an existing CAD geometry from the native CAD to the ACIS format. The ACIS format file is then cleaned using SpaceClaim to remove small holes and component overlaps. Metadata is then assigned to the cleaned geometry file using CUBIT/Trelis from csimsoft (Registered Trademark). The DAGMC plugin script removes duplicate shared surfaces, facets the geometry to a specified tolerance, and ensures that the faceted geometry is water tight. This step also writes the material and scoring information to a standard input file format that the analyst can alter as desired prior to running the radiation transport program. The scoring results can be transformed, via python script, into a 3D format that is viewable in a standard graphics program. RESULTS The CAD model of the US Lab module of the International Space Station, inclusive of all the racks and components, was simplified to remove holes and volume overlaps. Problematic features within the drawing were also removed or repaired to prevent runtime issues. The cleaned drawing was then run through the DAGMC workflow to prepare for analysis. Pilot tests modeling transport of 1GeV proton and 800MeV/A oxygen sources show that reasonable results are converged upon in an acceptable amount of overall computation time from drawing preparation to data analysis. The FLUKA radiation transport code will next be used to model both a GCR and a trapped radiation source. These results will then be compared with measurements that have been made by the radiation instrumentation deployed inside the US Lab module. DISCUSSION Early analyses have indicated that the DAGMC workflow is a promising toolkit for running vehicle geometries of interest to NASA through multiple radiation transport codes. In addition, recent work has shown that a realistic human phantom, provided via a subcontract with the University of Florida, can be placed inside any vehicle geometry for a combinatorial analysis. This added functionality gives the user the ability to score various parameters at the organ level, and the results can then be used as input for cancer risk models.

Barzilla, J. E.↗